Pipeline to Mapping RxNORM Codes with Their Corresponding UMLS Codes

Description

This pretrained pipeline is built on the top of rxnorm_umls_mapper model.

Predicted Entities

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Available as Private API Endpoint

Deploy

Deploy

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("rxnorm_umls_mapping", "en", "clinical/models")
result = pipeline.fullAnnotate(["1161611", "315677"])

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("rxnorm_umls_mapping", "en", "clinical/models")

val result = pipeline.fullAnnotate(["1161611", "315677"])

import nlu
nlu.load("en.rxnorm.umls.mapping").predict("""Put your text here.""")

Results

|   | rxnorm_code | umls_code |
|--:|------------:|----------:|
| 0 |     1161611 |  C3215948 |
| 1 |      315677 |  C0984912 |

Model Information

Included Models

• DocumentAssembler
• TokenizerModel
• ChunkMapperModel